Bruno MCP
브루노 MCP 서버
Bruno 컬렉션을 실행할 수 있는 MCP(Model Context Protocol) 서버입니다. 이 서버를 통해 LLM은 Bruno를 사용하여 API 테스트를 실행하고 표준화된 인터페이스를 통해 자세한 결과를 얻을 수 있습니다.
특징
Bruno CLI를 사용하여 Bruno 컬렉션 실행
환경 파일 지원
환경 변수 지원
다음을 포함한 자세한 테스트 결과:
전반적인 성공/실패 상태
시험 요약(전체, 합격, 불합격)
자세한 실패 정보
실행 타이밍
Related MCP server: bruno-mcp
설치
Smithery를 통해 설치
Smithery 를 통해 Claude Desktop에 Bruno MCP Server를 자동으로 설치하려면:
지엑스피1
수동 설치
# Install dependencies
npm install
# Build the project
npm run build구성
~/Library/Application Support/Claude/claude_desktop_config.json 에 있는 Claude 데스크톱 구성 파일에 서버를 추가합니다.
{
"mcpServers": {
"bruno-runner": {
"command": "npx",
"args": ["-y", "bruno-mcp"],
}
}
}사용 가능한 도구
런 컬렉션
Bruno 컬렉션을 실행하고 테스트 결과를 반환합니다.
매개변수:
collection(필수): Bruno 컬렉션 경로environment(선택 사항): 환경 파일 경로variables(선택 사항): 키-값 쌍으로 구성된 환경 변수
응답 예시:
{
"success": true,
"summary": {
"total": 5,
"failed": 0,
"passed": 5
},
"failures": [],
"timings": {
"started": "2024-03-14T10:00:00.000Z",
"completed": "2024-03-14T10:00:01.000Z",
"duration": 1000
}
}Claude에서의 사용 예
Claude에서 서버를 사용하려면 Bruno 컬렉션을 실행하도록 요청해야 합니다.
"/path/to/collection.bru에서 Bruno 컬렉션을 실행하고 모든 테스트가 통과되었는지 알려주세요"
클로드는 다음을 할 것입니다:
실행 수집 도구를 사용하세요
테스트 결과를 분석하다
실행에 대한 인간 친화적인 요약을 제공합니다.
개발
프로젝트 구조
src/
├── index.ts # Entry point
├── server.ts # MCP Server implementation
├── runner.ts # Bruno runner implementation
└── types.ts # Type definitions테스트 실행
# Run tests
npm test
# Run tests with coverage
npm test:coverage건물
# Build the project
npm run build
# Clean build artifacts
npm run clean특허
MIT
Available Tools
1 toolrun-collectionC
Run a Bruno Collection using Bruno CLI
| Name | Required | Description | Default |
|---|---|---|---|
| collection | Yes | Path to the Bruno collection | |
| environment | No | Optional path to environment file | |
| variables | No | Optional environment variables |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions 'Run' which implies execution, but fails to describe critical behaviors like whether it's read-only/destructive, requires specific permissions, has side effects (e.g., file changes), or handles errors. This leaves significant gaps for an execution tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence with zero wasted words. It's appropriately sized and front-loaded, clearly stating the core action without unnecessary elaboration.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of running a collection (an execution tool with potential side effects), no annotations, and no output schema, the description is incomplete. It lacks details on behavior, output format, error handling, or dependencies, making it inadequate for safe and effective use by an AI agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema description coverage is 100%, so the schema already documents all parameters (collection path, optional environment file, optional variables). The description adds no additional meaning beyond what the schema provides, such as format examples or usage context, meeting the baseline for high coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('Run') and resource ('a Bruno Collection using Bruno CLI'), making the purpose understandable. However, it doesn't differentiate from siblings since there are none, so it can't achieve the full 5 points for sibling differentiation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool, such as prerequisites (e.g., Bruno CLI installation), alternatives, or specific contexts. It only states what the tool does without usage instructions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
1 tool update
- First observed
run-collection
TDQS
Scored across 1 tool
With only one tool, there is no possibility of confusion or overlap between tools. The tool 'run-collection' has a single, clearly defined purpose that cannot be misselected against other tools.
Since there is only one tool, naming consistency is inherently perfect. The tool name 'run-collection' follows a verb-noun pattern, and there are no other tools to compare it against for inconsistency.
A single tool is generally too few for most server purposes, as it limits functionality and may indicate an incomplete or overly narrow scope. While it could be appropriate for a very specific task, it often feels thin and lacks the breadth needed for typical agent workflows.
With only one tool, the surface is severely incomplete. There are obvious gaps, such as the inability to create, list, update, or delete collections, which are typical operations in a collection management domain. This will likely cause agent failures when trying to perform basic tasks beyond running a collection.
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Related MCP Servers
- AlicenseBqualityFmaintenanceA Model Context Protocol (MCP) server that enables programmatic creation and management of Bruno API testing collections, environments, and requests through standardized MCP tools.161 npm35MIT
- AlicenseNot gradedqualityCmaintenanceMCP server that executes requests from Bruno API collections via the Bruno CLI tool, enabling API request execution and collection management.30 PyPI4MIT
- AlicenseAqualityBmaintenanceRead-only MCP server for indexing and searching Bruno API collections. Enables endpoint discovery and contract retrieval without executing requests.828 npmMIT
- AlicenseNot gradedqualityCmaintenanceA headless MCP server for Bruno workspaces, enabling CRUD operations on collections, folders, requests, environments, and dotenv files, plus request execution with scripting, tests, and assertions over HTTP, GraphQL, gRPC, and WebSocket.MIT